1. Technical Field
The present disclosure generally relates to the field of data processing and online advertising. More specifically, and without limitation, the exemplary embodiments described herein relate to systems and methods for generating expanded user segments for use in targeted online advertising.
2. Background
As greater numbers of people use the World Wide Web for communication, commerce, and other daily activities, they generate larger and larger volumes of traffic over the Internet. Because the benefits of commercializing the Internet can be tremendous, businesses increasingly take advantage of this traffic by advertising their products or services online. These advertisements may appear in the form of leased advertising space (e.g., “banners”) on content websites, which are operated by “publishers” who control the website content and the availability and cost of the advertising space or “ad inventory.”
Advertisers of various products or services may create online advertising campaigns that include advertisements designed to be placed on content websites during a specified period of time. For example, an automobile company may design several advertisements for a new model and may wish to have the advertisements placed online during a period surrounding the launch of the new model. Each time an advertisement is shown to a viewer of the website it is known as an “impression.” After an advertisement is shown, a user may select, or “click,” on the advertisement or may take another “action” such as completing an online form to request more information. If the user purchases the new model of automobile, the purchase is referred to as a “conversion” of the impression. Advertisers may pay owners of content websites (i.e., the publishers) based on, for example, the number of impressions, clicks, actions, or conversions in connection with an advertising campaign.
In some cases, an advertiser may have a marketing plan that identifies certain types of people as being target audience members for a given product or service. For example, the advertiser may wish to spend money only on users having certain demographics or personal interests. Alternatively, advertisers may be unsure of which people are most likely to respond to a given product, service, or advertisement. Therefore, advertisers may wish to obtain very specific information about the types of consumers viewing various types of websites and responding to advertisements. In some cases, advertisers may be willing to spend more money per impression, click, action, or conversion based on known information about those users interacting with the advertisements. As a result, publishers of content websites and/or facilitators of third party advertising networks may wish to obtain as much information as possible about consumers and other users traveling between web pages associated with an advertising network.
One way of analyzing the Internet audience is segmentation, the process of dividing the total user population into smaller, but homogenous segments, according to some specified characteristics, such as geographical location, demographics, behaviors and responses to campaigns. Such segments can be offered to online advertisers who are interested in targeting specific segments that are most appropriate for their online advertising campaigns. For example, advertisers may want to target an ad campaign to users who have clicked on a particular website or banner ad. In some cases, online advertisers may be willing to pay more money per impression, click, etc. for users that fall within those specific segments.
User segments with characteristics of interest to the online advertisers, however, are not always targetable in large numbers, because the actual population of such qualified users can be quite small. For example, advertisers may be interested in targeting people who have provided certain demographic information (e.g., to a social networking site), or clicked on a particular advertisement, etc. However, the actual population of such users may be relatively small compared to the total Internet population. In addition, user segments with characteristics of interest to the online advertisers may not be immediately available. For example, an advertiser may want to target users who are likely to convert to its campaigns (i.e., click an advertisement and/or make a purchase), but who have not yet done so. The identification of such segments may involve the prediction of user behavior in the future, which is not yet available.
The present disclosure is directed to achieving one or more of the above-referenced goals by providing improved systems and methods for online advertising. Among other features and advantages, the disclosed embodiments perform online user profiling, and generate expanded segments of online users.